World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
14911
World Ranking
7764
National Ranking
131

Overview

Michael S. Lew is affiliated with Leiden University in the Netherlands. Their research spans primarily the field of Computer Science, with a particular focus on subfields including Computer Vision and Pattern Recognition, Artificial Intelligence, Global and Planetary Change, Biomedical Engineering, and Demography.

Their scholarly output includes numerous papers addressing topics within multimodal machine learning, domain adaptation and few-shot learning, and advanced techniques for image and video retrieval. Their published works cover a range of subjects such as video surveillance and tracking methods, human pose and action recognition, as well as image enhancement techniques.

Frequent collaborators in their research include Erwin M. Bakker, Nan Pu, Wei Chen, Yu Liu, and Guoqiang Xiao. These partnerships reflect a broad collaborative network across related areas of study.

Michael S. Lew has published extensively in various academic venues. Notable frequent publication outlets include arXiv (Cornell University), the International Journal of Multimedia Information Retrieval, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Multimedia, and Engineering Applications of Artificial Intelligence.

Key recent papers authored or co-authored by Michael S. Lew include:

  • Deep Learning for Instance Retrieval: A Survey, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • A Memorizing and Generalizing Framework for Lifelong Person Re-Identification, 2023, IEEE Transactions on Pattern Analysis and Machine Intelligence
  • New Ideas and Trends in Deep Multimodal Content Understanding: A Review, 2020, Neurocomputing
  • Integrating information theory and adversarial learning for cross-modal retrieval, 2021, Pattern Recognition
  • Feature Estimations Based Correlation Distillation for Incremental Image Retrieval, 2021, IEEE Transactions on Multimedia

Main research topics covered by Michael S. Lew include:

  • Multimodal Machine Learning Applications
  • Domain Adaptation and Few-Shot Learning
  • Video Surveillance and Tracking Methods
  • Advanced Image and Video Retrieval Techniques
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Image Enhancement Techniques

Best Publications

  • Content-based multimedia information retrieval: State of the art and challenges

    Michael S. Lew;Nicu Sebe;Chabane Djeraba;Ramesh Jain

  • Deep learning for visual understanding

    Yanming Guo;Yu Liu;Ard Oerlemans;Songyang Lao

  • The MIR flickr retrieval evaluation

    Mark J. Huiskes;Michael S. Lew

  • A review of semantic segmentation using deep neural networks

    Yanming Guo;Yu Liu;Theodoros Georgiou;Michael S. Lew

  • Authentic facial expression analysis

    N. Sebe;M. S. Lew;Y. Sun;I. Cohen

  • New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative

    Mark J. Huiskes;Bart Thomee;Michael S. Lew

  • Image and Video Retrieval

    Wee-Kheng Leow;Michael S. Lew;Tat-Seng Chua;Wei-Ying Ma

  • Principles of Visual Information Retrieval

    Michael S. Lew

  • Deep Learning for Instance Retrieval: A Survey

    Unknown

  • Emotion recognition using a Cauchy Naive Bayes classifier

    N. Sebe;M.S. Lew;I. Cohen;A. Garg

  • The state of the art in image and video retrieval

    Nicu Sebe;Michael S. Lew;Xiang Zhou;Thomas S. Huang

  • Image retrieval using wavelet-based salient points

    Qi Tian;Nicu Sebe;Michael S. Lew;Etienne Loupias

  • Next-generation Web searches for visual content

    M.S. Lew

  • Learning and feature selection in stereo matching

    M.S. Lew;T.S. Huang;Kam Wong

  • Learning a Recurrent Residual Fusion Network for Multimodal Matching

    Yu Liu;Yanming Guo;Erwin M. Bakker;Michael S. Lew

  • Evaluation of salient point techniques

    Nicu Sebe;Qi Tian;Etienne Loupias;Michael S. Lew

  • A survey of traditional and deep learning-based feature descriptors for high dimensional data in computer vision

    Theodoros Georgiou;Yu Liu;Wei Chen;Michael S. Lew

  • Comparing salient point detectors

    Nicu Sebe;Michael S. Lew

  • Toward improved ranking metrics

    N. Sebe;M.S. Lew;D.P. Huijsmans

  • CNN-RNN: a large-scale hierarchical image classification framework

    Yanming Guo;Yu Liu;Erwin M. Bakker;Yuanhao Guo

  • The distributed ASCI Supercomputer project

    Henri Bal;Raoul Bhoedjang;Rutger Hofman;Ceriel Jacobs

  • Authentic facial expression analysis

    N. Sebe;M.S. Lew;I. Cohen;Yafei Sun

  • Facial expression recognition from video sequences

    I. Cohen;N. Sebe;A. Garg;M.S. Lew

Frequent Co-Authors

Nicu Sebe
Nicu Sebe University of Trento
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Ira Cohen
Ira Cohen Hewlett-Packard (United States)
Qi Tian
Qi Tian Huawei Technologies (China)
Thomas Bäck
Thomas Bäck Leiden University
Vladimir Pavlovic
Vladimir Pavlovic Rutgers, The State University of New Jersey
Theo Gevers
Theo Gevers University of Amsterdam
Kin-Man Lam
Kin-Man Lam Hong Kong Polytechnic University
Tat-Seng Chua
Tat-Seng Chua National University of Singapore

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